Despite the widespread adoption and popularity of social media, research on measuring the quantifiable impact of popular social media platforms remains scarce. To this end, this study attempts to investigate how the influence of social media can be assessed in quantitative terms. The main objective is to develop a new assessment model able to integrate a broad range of criteria such as likes, subscribers, comments, posts, shares, and links. The authors extend previous assessment models focused on individual platforms such as blogs and propose a Social Media Influence Assessment model (SMIA). The process of model development—criteria, dimensions, and formula—and its validation are discussed. The results indicate that social media's influence can be measured in a structured, quantifiable manner by utilising a set of nine criteria grouped into three dimensions: recognition, activity generation, and credibility.
TopIntroduction
The social media phenomenon is rapidly changing the way Internet users connect with each other, share opinions, create special interest groups and communities of interest, debate on certain issues, collaborate, and influence each other’s thoughts and opinions (Kaplan & Haenlein, 2010). Popular social media platforms such as Facebook, Twitter, LinkedIn, YouTube, blogging services, Google+, and Pinterest have become firmly entrenched in people’s everyday lives and are widely used to exchange news, opinions, and random thoughts, as well as to share photos and videos, search for friends, share experiences, express sentiments, and seek advice in a time of need. At the same time, many business executives view social media as an important advertising and marketing instrument and put social media strategies at the top of their agendas (Jadhav, Kamble, & Patil, 2013; Kaplan & Haenlein, 2010; Tuten & Solomon, 2014). The impact and influence of user-driven media should not be underestimated since research shows that digital technologies are often used in innovative ways by professionals and common Internet users alike (Couldry, 2012; Gillmore, 2006; Hassan, 2013; Keller & Berry, 2003). Despite the widespread adoption of social interaction technologies, research that examines the impact of social media based on quantifiable parameters is scarce. Part of the problem is the lack of reliable metrics. Therefore, there is a need for research on how to measure the impact and influence of social media sites. Such studies may benefit the research community as a whole; furthermore, it may also help business firms that turn to social media as a marketing tool. Social commerce can particularly benefit from more focused attention from scholars in the field of information systems to social media quantification (Chingning & Ping, 2012).
Existing website performance metrics and analytics are not quite suitable for social media assessment due to the nature of technology and its usage (Agarwal & Liu, 2008; Hassan, Shiratuddin, Sakdan, Hashim, & Sajat, 2012). In addition, most ranking algorithms employed in ranking websites are based on a limited number of criteria such as page hits or number of visitors. Consequently, introducing additional criteria such as number of inlinks, number of outlinks, number of posts, and number of comments (Shiratuddin et al., 2011) may be beneficial. It has been suggested by the authors of this paper that limiting the criteria for measuring social media’s influence may be inconclusive and unproductive.
Previously, several measurement tools have been designed for evaluating the impact of mass media on audiences. Audit Bureaus of Circulation (ABC),1 industry-sponsored organizations operating in 40 national markets under the umbrella of the International Federation of Audit Bureaux of Circulations (IFABC), have developed standards for measuring the circulation of first print and then digital media. ComScore, Alexa, Nielsen Online, and other digital data analytics companies provide instruments for measuring online audiences. ComScore, for example, uses audience size and reach as criteria for measurement (Ries, 2012). Its measurement methodology, Unified Digital Measurement (UDM) integrates person-centric data obtained from online recruited panellists and server centric census data supplied by monitoring applications installed on nearly 2 million users’ computers (ComScore, 2013). However, when measuring the influence of social media, additional criteria are needed because of its interactive nature. The role of individuals in distributing messages and building networks of relationships, size of the target audience, different types of responses, and the degree of influence in the community should also be taken into consideration.
The purpose of this study was to identify relevant criteria and develop a model for measuring social media’s influence in a structured, quantitative manner. By integrating quantitative measures, the authors ensure that the resulting model can be converted into an automated tool in the future.